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Compilation, validation, and analysis of integrated multi-dimensional datasets of international bilateral relations

  • Tipologia di contratto prestazione occasionale
  • Id bando 3956
  • Proponente Giorgio Fagiolo
  • Stato archivio
  • Soggetto Istituto di Economia
  • N. Assegni/Posizioni 1
  • Durata 2 mesi
  • Data pubblicazione bando 11.12.2023
  • Termine presentazione domanda 09.01.2024
  • Data pubblicazione graduatoria 11.01.2024 - 16:33
  • Sede dei colloqui

    Italia

Istituto di Economia: Avviso per conferimento 1 incarico di prestazione occasionale, 2 mesi per attivita' di supporto alla ricerca nell'ambito del progetto PRO3 (NetRes), consistente nella creazione di un database integrato multi-dimensionale di relazioni internazionali. Le attivita' comprenderanno: This set of tasks aims at compiling, validating, and analyzing a panel datasets describing how world countries interact along a number of dimensions, including trade of goods and services, foreign-direct investments, finance, human migration and mobility, patenting activities. All raw databases have been already independently collected within the PRO3 project NetRes and some of them have been explored, leading to a peer-review publication. The candidate is requested to: (i) harmonize and clean a large number of pre-existing databases; (ii) merge them into a final panel database of international relations characterizing the macroeconomic multi network; (iii) validate the resulting dataset using statistical techniques in order to check its consistency both internally (e.g., across similar layers and time) and externally (e.g., vis-à-vis alternative databases and/or aggregate macroeconomic indicators); (iv) generate a number of rescaled and normalized versions of the database that may be helpful for network analysis; (v) provide a preliminary descriptive analysis of the resulting database in terms of its topological network structure. The candidate is expected to: (a) have accumulated previous experience (e.g., during her/his dissertation or previous research activity) in dealing with large sets of network data; (b) know tools and techniques related to applied network science: (c) be familiar with statistical and econometric software packages (e.g, R and/or Stata), especially as far as implementation of tasks (i)-(v) are concerned.